Lead Data Scientist
$180,000 | New York | Permanent
Posted +1 month ago
LEAD DATA SCIENTIST| MANHATTAN, NEW YORK
Key Skills: Statistical modelling, linear regression, tree models, regularization techniques, R and Python.
Exciting Lead Data Scientist opportunity based in Manhattan for a large Insurance company has arisen due to company evolution. This opportunity will see you working within the Data Science and Analytics group where they create and design data driven solutions for many parts of the business!
As the Lead Data Scientist, you will be:
* Leading the Data Analysis and Modeling projects
* Working with Key Stakeholders and demonstrating how Analytics can be implemented effectively in the business.
* Building Advanced statistical models and testing the methods
WHAT ARE THEY LOOKING FOR
* 5 Years + in statistical modelling techniques such as linear regression, logistic regression, survival analysis, GLM, tree models (Random Forests, GBM), cluster analysis, principal components, feature creation
* Insurance experience
* Strong expertise in regularization
* Excellent communication skills (consultative approach )
* Strong programming experience with Python and R and one or more of the following SAS, Spark, SQL, Hadoop, H20.
WHY SHOULD I APPLY
An amazing opportunity to join a US household name, who have a great reputation in the industry
The chance to work with the latest data science techniques
Salary up to $180,000 plus great benefits
Please submit your resume at the earliest should you wish to be considered for this role.
You must have the right to work in the United States to be considered for this opportunity
No third parties
InterQuest Group is acting as an employment agency for this vacancy. InterQuest Group is an equal opportunities employer and we welcome applications from all suitably qualified persons regardless of age, disability, gender, religion/belief, race, marriage, civil partnership, pregnancy, maternity, sex or sexual orientation. Please make us aware if you require any reasonable adjustments throughout the recruitment process.